期刊
SENSORS
卷 20, 期 7, 页码 -出版社
MDPI
DOI: 10.3390/s20072110
关键词
rowing sport; motion reconstruction; inertial sensor; data fusion
资金
- National Natural Science Foundation of China [61473058, 61873044, 61803072]
- Dalian Science and Technology Innovation fund [2018J12SN077]
- China Postdoctoral Science Foundation [2017M621131, 2017M621132]
- Liaoning Key R&D Guidance Project [ZX2018KJ002]
Coaches and athletes are constantly seeking novel training methodologies in an attempt to improve athletic performance. This paper proposes a method of rowing sport capture and analysis based on Inertial Measurement Units (IMUs). A canoeist's motion was collected by multiple miniature inertial sensor nodes. The gradient descent method was used to fuse data and obtain the canoeist's attitude information after sensor calibration, and then the motions of canoeist's actions were reconstructed. Stroke quality was performed based on the estimated joint angles. Machine learning algorithm was used as the classification method to divide the stroke cycle into different phases, including propulsion-phase and recovery-phase, a quantitative kinematic analysis was carried out. Experiments conducted in this paper demonstrated that our method possesses the capacity to reveal the similarities and differences between novice and coach, the whole process of canoeist's motions can be analyzed with satisfactory accuracy validated by videography method. It can provide quantitative data for coaches or athletes, which can be used to improve the skills of rowers.
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